Neuromonitoring is a subfield of clinical patient monitoring focused on measuring various aspects of brain function and on changes therein caused by drugs commonly used to induce and maintain anesthesia in an operation room or sedation in patients under critical or intensive care.
Electroencephalography (EEG) is a well-established method for assessing brain activity. When measurement electrodes are attached on the skin of the skull surface, the weak biopotential signals generated in the pyramid cells of the cortex may be recorded and analyzed. The EEG has been in wide use for decades in basic research of the neural systems of the brain as well as in the clinical diagnosis of various central nervous system diseases and disorders.
Electromyography (EMG) is a method for recording electrical biopotentials of muscles. In an EMG measurement, the electrodes are attached onto the surface of the skin overlying a muscle. When a biopotential signal is recorded from the forehead of a subject, the recorded signal indicates both the activity of the facial muscles (fEMG) and the brain (EEG).
One of the special applications of the EEG, which has received attention recently, is the use of a processed EEG signal for objective quantification of the amount and type of brain activity for the purpose of determining the level of consciousness of a patient. In its simplest form, the utilization of an EEG signal allows the automatic detection of the alertness of an individual, i.e. if he or she is awake or asleep. This has become an issue of increased interest, both scientifically and commercially, in the context of measuring the depth of unconsciousness induced by anesthesia during surgery.
Another important component of balanced anesthesia is analgesia, i.e. prevention of pain reactions of a patient by administration of pain medication. Adequate analgesia reduces surgical stress and there is firm evidence that it decreases postoperative morbidity. Awareness during surgery with insufficient analgesia may lead to a post-traumatic stress disorder. Low quality pre- and intra-operative analgesia makes it difficult to select the optimal pain management strategy later on. More specifically, it may cause exposure to unwanted side effects during the recovery from the surgery. If the anesthesia is too light and involves insufficient hypnosis, it may cause traumatic experiences both for the patient and for the anesthesia personnel. From an economical point of view, if the anesthesia is too deep, it may cause increased perioperative costs through extra use of drugs and time, and extend the time required for post-operative care.
Virtually every patient being cared for in an intensive care unit (ICU), for example, receives some form of sedation. However, the control of the depth of the sedation administered to a patient is still problematic, and therefore oversedation and undersedation are both common occurrences in intensive care units. At present, monitoring the level of sedation is mainly handled by using subjective observations from the patient. Various sedation assessment scales have been developed for subjectively assessing the level of sedation, the Ramsay Score being one of the most widely used tools for this purpose.
The depth of hypnosis is not directly measurable. Therefore, drug delivery systems have to derive the level of hypnosis from a surrogate signal or from indirectly measured parameters. The most common and popular surrogate signal for this purpose is the EEG, from which several parameters may be determined. The basic reason for the insufficiency of a single parameter is the variety of drugs and the complexity of the drug effects on the EEG signal in human brains. However, during the past few years, some commercial validated devices for measuring the level of consciousness and/or awareness in clinical set-up during anesthesia or sedation have become available. Such devices, which are based on a processed EEG signal and examine the signal as a whole with its multiple features, are marketed by GE Healthcare Finland Oy, Kuortaneenkatu 2, FIN-00510 Helsinki (Entropy Index) and by Aspect Medical Systems, Inc., 141 Needham Street, Newton, Mass. 02464, U.S.A. (Bispectral Index, BIS™).
In addition to the EEG signal data, EMG signal data obtained from facial muscles (fEMG) of the forehead is used for monitoring purposes during anesthesia and intensive care. Recovering facial muscle activity is often the first indicator of the patient approaching consciousness. When this muscle activity is sensed by electrodes placed appropriately, it provides an early indication that the patient is emerging from anesthesia. Similarly, these electrodes can sense pain reactions when the anesthesia is not adequate due to inadequate analgesia. So, the EMG signals give an early warning of the arousal of the patient, and they may also be indicative of inadequate analgesia.
Several factors affect the state of the central nervous system (CNS) of an ICU patient: sedative drugs, natural sleep cycles, and brain disorders all have their effect on the EEG signal. So far, no methods exist to distinguish these components from each other to provide a clinician an overall picture of the CNS state of the patient. The development of such a method is challenging due to the non-specificity of the EEG signal. A slow wave EEG pattern, for example, may be associated with a high level of a sedative, deep natural sleep, or a severe stage of encephalopathy. Correspondingly, low EEG entropy or BIS levels may be associated with any of these causes. Furthermore, natural variations of vigilance cause high fluctuations of entropy or BIS that tend to mask any underlying information of the sedative drug effect. Therefore, the above-mentioned devices for measuring the level of (un)consciousness and/or (un)awareness are not suitable for distinguishing the different causes giving rise to the level measured.
The clinician can distinguish between the different causes by including contextual information and by stimulating the patient. For example, if a patient with a slow wave EEG has not received substantial amounts of sedative drugs and has normally functioning liver/kidneys, he cannot be too deeply sedated. If the patient in such a situation anyway does not respond to a strong external stimulus, the clinician may conclude that the patient has developed a brain disorder. To estimate the sedative drug effect and particularly to avoid too deep levels of sedation, it is recommended that some kind of stimulus-response-based scoring is regularly performed by the nursing staff. Such scores are, however, often imprecise and subjective and do not provide continuous information. Furthermore, stimulus-response-based scoring is difficult to implement in automatic monitoring.
The present invention seeks to alleviate or eliminate the above-mentioned drawbacks.